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Full-Text Articles in Mathematics
Characterizations And Infinite Divisibility Of Certain Recently Introduced Distributions Iv, Gholamhossein G. Hamedani
Characterizations And Infinite Divisibility Of Certain Recently Introduced Distributions Iv, Gholamhossein G. Hamedani
Mathematics, Statistics and Computer Science Faculty Research and Publications
Certain characterizations of recently proposed univariate continuous distributions are presented in different directions. This work contains a good number of reintroduced distributions and may serve as a source of preventing the reinvention and/or duplication of the existing distributions in the future.
Type I General Exponential Class Of Distributions, Gholamhossein G. Hamedani, Haitham M. Yousof, Mahdi Rasekhi, Morad Alizadeh, Seyed Morteza Najibi
Type I General Exponential Class Of Distributions, Gholamhossein G. Hamedani, Haitham M. Yousof, Mahdi Rasekhi, Morad Alizadeh, Seyed Morteza Najibi
Mathematics, Statistics and Computer Science Faculty Research and Publications
We introduce a new family of continuous distributions and study the mathematical properties of the new family. Some useful characterizations based on the ratio of two truncated moments and hazard function are also presented. We estimate the model parameters by the maximum likelihood method and assess its performance based on biases and mean squared errors in a simulation study framework.
New Classes Of Univariate Continuous Exponential Power Series Distributions, M. Ahsanullah, Gholamhossein G. Hamedani, M. Shakil, B.M. Golam Kibria, F. George
New Classes Of Univariate Continuous Exponential Power Series Distributions, M. Ahsanullah, Gholamhossein G. Hamedani, M. Shakil, B.M. Golam Kibria, F. George
Mathematics, Statistics and Computer Science Faculty Research and Publications
Recently, many researchers have developed various classes of continuous probability distributions which can be generated via the generalized Pearson differential equation and other techniques. In this paper, motivated by the importance of the power series in probability theory and its applications, we derive some new classes of univariate exponential power series distributions for a realvalued continuous random variable, which we call exponential power series distributions. Various mathematical properties of the proposed classes of distributions are discussed. Based on these distributional properties, we have established some characterizations of these distributions as well. It is hoped that the findings of the paper …
A New Weibull-G Family Of Distributions, M. H. Tahir, Muhammad Zubair, M. Mansoor, Gauss M. Cordeiro, Morad Alizadeh, Gholamhossein Hamedani
A New Weibull-G Family Of Distributions, M. H. Tahir, Muhammad Zubair, M. Mansoor, Gauss M. Cordeiro, Morad Alizadeh, Gholamhossein Hamedani
Mathematics, Statistics and Computer Science Faculty Research and Publications
Statistical analysis of lifetime data is an important topic in reliability engineering, biomedical and social sciences and others. We introduce a new generator based on the Weibull random variable called the new Weibull-G family. We study some of its mathematical properties. Its density function can be symmetrical, left-skewed, right-skewed, bathtub and reversed-J shaped, and has increasing, decreasing, bathtub, upside-down bathtub, J, reversed-J and S shaped hazard rates. Some special models are presented. We obtain explicit expressions for the ordinary and incomplete moments, quantile and generating functions, Renyi entropy, order statistics and reliability. Three useful characterizations based on truncated moments are …
A Generalized Gamma-Weibull Distribution: Model, Properties And Applications, R. S. Meshkat, H. Torabi, Gholamhossein G. Hamedani
A Generalized Gamma-Weibull Distribution: Model, Properties And Applications, R. S. Meshkat, H. Torabi, Gholamhossein G. Hamedani
Mathematics, Statistics and Computer Science Faculty Research and Publications
We prepare a new method to generate family of distributions. Then, a family of univariate distributions generated by the Gamma random variable is defined. The generalized gamma-Weibull (GGW) distribution is studied as a special case of this family. Certain mathematical properties of moments are provided. To estimate the model parameters, the maximum likelihood estimators and the asymptotic distribution of the estimators are discussed. Certain characterizations of GGW distribution are presented. Finally, the usefulness of the new distribution, as well as its effectiveness in comparison with other distributions, are shown via an application of a real data set.
Characterizations Of Transmuted Complementary Weibull Geometric Distribution, Gholamhossein Hamedani
Characterizations Of Transmuted Complementary Weibull Geometric Distribution, Gholamhossein Hamedani
Mathematics, Statistics and Computer Science Faculty Research and Publications
We present certain characterizations of a recently introduced distribution (Afify et al., 2014), called Transmuted Complementary Weibull Geometric distribution based on: hazard function ; a simple relation between two truncated moments. We like to mention that the characterization which is expressed in terms of the ratio of truncated moments is stable in the sense of weak convergence. It does not require a closed form for the cumulative distribution function and serves as a bridge between a first order differential equation and probability.
Remarks On Characterizations Of Malinowska And Szynal, Gholamhossein Hamedani, Z. Javanshiri, Mehdi Maadooliat, A. Yazdani
Remarks On Characterizations Of Malinowska And Szynal, Gholamhossein Hamedani, Z. Javanshiri, Mehdi Maadooliat, A. Yazdani
Mathematics, Statistics and Computer Science Faculty Research and Publications
The problem of characterizing a distribution is an important problem which has recently attracted the attention of many researchers. Thus, various characterizations have been established in many different directions. An investigator will be vitally interested to know if their model fits the requirements of a particular distribution. To this end, one will depend on the characterizations of this distribution which provide conditions under which the underlying distribution is indeed that particular distribution. In this work, several characterizations of Malinowska and Szynal (2008) for certain general classes of distributions are revisited and simpler proofs of them are presented. These characterizations are …
Mcdonald Log-Logistic Distribution With An Application To Breast Cancer Data, M. H. Tahir, Muhammad Mansoor, Muhammad Zubair, Gholamhossein Hamedani
Mcdonald Log-Logistic Distribution With An Application To Breast Cancer Data, M. H. Tahir, Muhammad Mansoor, Muhammad Zubair, Gholamhossein Hamedani
Mathematics, Statistics and Computer Science Faculty Research and Publications
We introduce a five-parameter continuous model, called the McDonald log-logistic distribution, to extend the two-parameter log-logistic distribution. Some structural properties of this new distribution such as reliability measures and entropies are obtained. The model parameters are estimated by the method of maximum likelihood using L-BFGS-B algorithm. A useful characterization of the distribution is proposed which does not require explicit closed form of the cumulative distribution function and also connects the probability density function with a solution of a first order differential equation. An application of the new model to real data set shows that it can give consistently better fit …
Characterizations Of New Modified Weibull Distribution, Gholamhossein Hamedani
Characterizations Of New Modified Weibull Distribution, Gholamhossein Hamedani
Mathematics, Statistics and Computer Science Faculty Research and Publications
Several characterizations of a New Modified Weibull distribution, introduced by Doostmoradi et al. (2014), are presented. These characterizations are based on: (i) truncated moment of a function of the random variable; (ii) the hazard function; (iii) a single function of the random variable; (iv) truncated moment of certain function of the 1st order statistic.